Dataset statistics
| Number of variables | 14 |
|---|---|
| Number of observations | 111857 |
| Missing cells | 2694 |
| Missing cells (%) | 0.2% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 11.9 MiB |
| Average record size in memory | 112.0 B |
Variable types
| Categorical | 5 |
|---|---|
| Numeric | 9 |
User Comments Added has constant value "0" | Constant |
Date has a high cardinality: 1523 distinct values | High cardinality |
Video Title has a high cardinality: 223 distinct values | High cardinality |
External Video ID has a high cardinality: 223 distinct values | High cardinality |
Thumbnail link has a high cardinality: 223 distinct values | High cardinality |
Video Length is highly correlated with Average View Percentage | High correlation |
Views is highly correlated with Video Likes Added and 1 other fields | High correlation |
Video Likes Added is highly correlated with Views and 1 other fields | High correlation |
User Subscriptions Added is highly correlated with Views and 1 other fields | High correlation |
Average View Percentage is highly correlated with Video Length | High correlation |
Views is highly correlated with Video Likes Added and 3 other fields | High correlation |
Video Likes Added is highly correlated with Views and 2 other fields | High correlation |
Video Dislikes Added is highly correlated with Views and 1 other fields | High correlation |
Video Likes Removed is highly correlated with Video Dislikes Added | High correlation |
User Subscriptions Added is highly correlated with Views and 1 other fields | High correlation |
User Subscriptions Removed is highly correlated with Views and 1 other fields | High correlation |
Views is highly correlated with Video Likes Added | High correlation |
Video Likes Added is highly correlated with Views and 1 other fields | High correlation |
User Subscriptions Added is highly correlated with Video Likes Added | High correlation |
Views is highly correlated with Video Likes Added and 4 other fields | High correlation |
Video Likes Added is highly correlated with Views and 4 other fields | High correlation |
Video Dislikes Added is highly correlated with Views and 4 other fields | High correlation |
Video Likes Removed is highly correlated with Views and 2 other fields | High correlation |
User Subscriptions Added is highly correlated with Views and 3 other fields | High correlation |
User Subscriptions Removed is highly correlated with Views and 3 other fields | High correlation |
Average View Percentage has 1347 (1.2%) missing values | Missing |
Average Watch Time has 1347 (1.2%) missing values | Missing |
Views is highly skewed (γ1 = 43.93953763) | Skewed |
Video Likes Added is highly skewed (γ1 = 36.19381899) | Skewed |
Video Dislikes Added is highly skewed (γ1 = 139.9320946) | Skewed |
Video Likes Removed is highly skewed (γ1 = 190.5669346) | Skewed |
User Subscriptions Added is highly skewed (γ1 = 70.58319419) | Skewed |
User Subscriptions Removed is highly skewed (γ1 = 31.48082153) | Skewed |
Views has 1347 (1.2%) zeros | Zeros |
Video Likes Added has 69081 (61.8%) zeros | Zeros |
Video Dislikes Added has 109015 (97.5%) zeros | Zeros |
Video Likes Removed has 106332 (95.1%) zeros | Zeros |
User Subscriptions Added has 86412 (77.3%) zeros | Zeros |
User Subscriptions Removed has 110050 (98.4%) zeros | Zeros |
Reproduction
| Analysis started | 2022-04-04 01:11:15.524517 |
|---|---|
| Analysis finished | 2022-04-04 01:11:37.139823 |
| Duration | 21.62 seconds |
| Software version | pandas-profiling v3.1.0 |
| Download configuration | config.json |
| Distinct | 1523 |
|---|---|
| Distinct (%) | 1.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 874.0 KiB |
| 4 Oct 2021 | 202 |
|---|---|
| 20 Sept 2021 | 201 |
| 27 Dec 2021 | 192 |
| 29 Dec 2021 | 190 |
| 30 Dec 2021 | 190 |
| Other values (1518) |
Length
| Max length | 12 |
|---|---|
| Median length | 11 |
| Mean length | 10.79518492 |
| Min length | 10 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 294 ? |
|---|---|
| Unique (%) | 0.3% |
Sample
| 1st row | 19 Jan 2022 |
|---|---|
| 2nd row | 19 Jan 2022 |
| 3rd row | 19 Jan 2022 |
| 4th row | 19 Jan 2022 |
| 5th row | 19 Jan 2022 |
Common Values
| Value | Count | Frequency (%) |
| 4 Oct 2021 | 202 | 0.2% |
| 20 Sept 2021 | 201 | 0.2% |
| 27 Dec 2021 | 192 | 0.2% |
| 29 Dec 2021 | 190 | 0.2% |
| 30 Dec 2021 | 190 | 0.2% |
| 6 Jan 2022 | 189 | 0.2% |
| 16 Jan 2022 | 189 | 0.2% |
| 19 Dec 2021 | 189 | 0.2% |
| 18 Jan 2022 | 189 | 0.2% |
| 23 Dec 2021 | 188 | 0.2% |
| Other values (1513) | 109938 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| 2021 | 61222 | |
| 2020 | 39267 | 11.7% |
| dec | 11614 | 3.5% |
| nov | 10940 | 3.3% |
| oct | 10863 | 3.2% |
| sept | 10123 | 3.0% |
| jan | 10081 | 3.0% |
| aug | 10065 | 3.0% |
| jul | 9614 | 2.9% |
| jun | 8772 | 2.6% |
| Other values (39) | 153010 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 223 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 874.0 KiB |
| Predicting Crypto-Currency Price Using RNN lSTM & GRU | 1522 |
|---|---|
| How to Simulate NBA Games in Python | 1105 |
| How I Became A Data Scientist From a Business Background | 1046 |
| Should You Get A Masters in Data Science? | 1029 |
| Work From Home Data Scientist: Day in the Life | 1015 |
| Other values (218) |
Length
| Max length | 100 |
|---|---|
| Median length | 53 |
| Mean length | 53.70190511 |
| Min length | 21 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | Kaggle Project From Scratch - Part 2 (Exploratory Data Analysis) |
|---|---|
| 2nd row | Welcome To My Channel | Ken Jee | Data Science |
| 3rd row | How She Dominated the FAANG Data Science Interview (@Tina Huang ) - KNN EP. 11 |
| 4th row | The 9 Books That Changed My Perspective in 2019 |
| 5th row | Interview with the Director of AI Research @ NVIDIA (Anima Anandkumar) - KNN EP. 07 |
Common Values
| Value | Count | Frequency (%) |
| Predicting Crypto-Currency Price Using RNN lSTM & GRU | 1522 | 1.4% |
| How to Simulate NBA Games in Python | 1105 | 1.0% |
| How I Became A Data Scientist From a Business Background | 1046 | 0.9% |
| Should You Get A Masters in Data Science? | 1029 | 0.9% |
| Work From Home Data Scientist: Day in the Life | 1015 | 0.9% |
| Scrape Twitter Data in Python with Twitterscraper Module | 1005 | 0.9% |
| Predicting Season Long NBA Wins Using Multiple Linear Regression | 974 | 0.9% |
| Should You Learn R for Data Science? | 973 | 0.9% |
| My Top 5 Data Science Resources for 2019 | 951 | 0.9% |
| Where YOU Should Start With Data Science Projects | 947 | 0.8% |
| Other values (213) | 101290 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| data | 100150 | 9.7% |
| science | 76061 | 7.4% |
| 38835 | 3.8% | |
| to | 25369 | 2.5% |
| a | 25312 | 2.5% |
| the | 24176 | 2.4% |
| how | 20324 | 2.0% |
| your | 15043 | 1.5% |
| projects | 14899 | 1.4% |
| you | 14684 | 1.4% |
| Other values (610) | 673514 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 223 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 874.0 KiB |
| qfRhKHV8-t4 | 1522 |
|---|---|
| irjTWNV0eAY | 1105 |
| IFceyuL6GZY | 1046 |
| RRSRKf9eQxc | 1029 |
| 4CpmB4TR2C4 | 1015 |
| Other values (218) |
Length
| Max length | 11 |
|---|---|
| Median length | 11 |
| Mean length | 11 |
| Min length | 11 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | KQ80oD_boBM |
|---|---|
| 2nd row | smeFkHwnM_k |
| 3rd row | vfV4nm004VQ |
| 4th row | 3TrAYmrmA8o |
| 5th row | Xgg7dIKys9E |
Common Values
| Value | Count | Frequency (%) |
| qfRhKHV8-t4 | 1522 | 1.4% |
| irjTWNV0eAY | 1105 | 1.0% |
| IFceyuL6GZY | 1046 | 0.9% |
| RRSRKf9eQxc | 1029 | 0.9% |
| 4CpmB4TR2C4 | 1015 | 0.9% |
| zF_Q2v_9zKY | 1005 | 0.9% |
| Y_SMU701qlA | 974 | 0.9% |
| AxP1CL0yaFQ | 973 | 0.9% |
| tv1e22u2COk | 951 | 0.9% |
| sq5TnVJWv6A | 947 | 0.8% |
| Other values (213) | 101290 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| qfrhkhv8-t4 | 1522 | 1.4% |
| irjtwnv0eay | 1105 | 1.0% |
| ifceyul6gzy | 1046 | 0.9% |
| rrsrkf9eqxc | 1029 | 0.9% |
| 4cpmb4tr2c4 | 1015 | 0.9% |
| zf_q2v_9zky | 1005 | 0.9% |
| y_smu701qla | 974 | 0.9% |
| axp1cl0yafq | 973 | 0.9% |
| tv1e22u2cok | 951 | 0.9% |
| sq5tnvjwv6a | 947 | 0.8% |
| Other values (213) | 101290 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 202 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 874.6158756 |
| Minimum | 47 |
|---|---|
| Maximum | 5029 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 47 |
|---|---|
| 5-th percentile | 216 |
| Q1 | 375 |
| median | 548 |
| Q3 | 917 |
| 95-th percentile | 2686 |
| Maximum | 5029 |
| Range | 4982 |
| Interquartile range (IQR) | 542 |
Descriptive statistics
| Standard deviation | 861.2976669 |
|---|---|
| Coefficient of variation (CV) | 0.9847725052 |
| Kurtosis | 4.773003066 |
| Mean | 874.6158756 |
| Median Absolute Deviation (MAD) | 211 |
| Skewness | 2.194913609 |
| Sum | 97831908 |
| Variance | 741833.671 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 467 | 1933 | 1.7% |
| 375 | 1757 | 1.6% |
| 311 | 1522 | 1.4% |
| 495 | 1484 | 1.3% |
| 484 | 1397 | 1.2% |
| 291 | 1383 | 1.2% |
| 392 | 1333 | 1.2% |
| 59 | 1277 | 1.1% |
| 378 | 1214 | 1.1% |
| 556 | 1105 | 1.0% |
| Other values (192) | 97452 |
| Value | Count | Frequency (%) |
| 47 | 224 | 0.2% |
| 51 | 474 | 0.4% |
| 53 | 212 | 0.2% |
| 55 | 6 | < 0.1% |
| 56 | 436 | 0.4% |
| 57 | 41 | < 0.1% |
| 59 | 1277 | |
| 60 | 167 | 0.1% |
| 114 | 169 | 0.2% |
| 128 | 427 | 0.4% |
| Value | Count | Frequency (%) |
| 5029 | 149 | 0.1% |
| 5005 | 153 | 0.1% |
| 4518 | 478 | |
| 4119 | 651 | |
| 4112 | 555 | |
| 3735 | 96 | 0.1% |
| 3706 | 428 | |
| 3659 | 367 | |
| 3493 | 398 | |
| 3413 | 168 | 0.2% |
| Distinct | 223 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 874.0 KiB |
| https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 1522 |
|---|---|
| https://i.ytimg.com/vi/irjTWNV0eAY/hqdefault.jpg | 1105 |
| https://i.ytimg.com/vi/IFceyuL6GZY/hqdefault.jpg | 1046 |
| https://i.ytimg.com/vi/RRSRKf9eQxc/hqdefault.jpg | 1029 |
| https://i.ytimg.com/vi/4CpmB4TR2C4/hqdefault.jpg | 1015 |
| Other values (218) |
Length
| Max length | 48 |
|---|---|
| Median length | 48 |
| Mean length | 48 |
| Min length | 48 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | https://i.ytimg.com/vi/KQ80oD_boBM/hqdefault.jpg |
|---|---|
| 2nd row | https://i.ytimg.com/vi/smeFkHwnM_k/hqdefault.jpg |
| 3rd row | https://i.ytimg.com/vi/vfV4nm004VQ/hqdefault.jpg |
| 4th row | https://i.ytimg.com/vi/3TrAYmrmA8o/hqdefault.jpg |
| 5th row | https://i.ytimg.com/vi/Xgg7dIKys9E/hqdefault.jpg |
Common Values
| Value | Count | Frequency (%) |
| https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 1522 | 1.4% |
| https://i.ytimg.com/vi/irjTWNV0eAY/hqdefault.jpg | 1105 | 1.0% |
| https://i.ytimg.com/vi/IFceyuL6GZY/hqdefault.jpg | 1046 | 0.9% |
| https://i.ytimg.com/vi/RRSRKf9eQxc/hqdefault.jpg | 1029 | 0.9% |
| https://i.ytimg.com/vi/4CpmB4TR2C4/hqdefault.jpg | 1015 | 0.9% |
| https://i.ytimg.com/vi/zF_Q2v_9zKY/hqdefault.jpg | 1005 | 0.9% |
| https://i.ytimg.com/vi/Y_SMU701qlA/hqdefault.jpg | 974 | 0.9% |
| https://i.ytimg.com/vi/AxP1CL0yaFQ/hqdefault.jpg | 973 | 0.9% |
| https://i.ytimg.com/vi/tv1e22u2COk/hqdefault.jpg | 951 | 0.9% |
| https://i.ytimg.com/vi/sq5TnVJWv6A/hqdefault.jpg | 947 | 0.8% |
| Other values (213) | 101290 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| https://i.ytimg.com/vi/qfrhkhv8-t4/hqdefault.jpg | 1522 | 1.4% |
| https://i.ytimg.com/vi/irjtwnv0eay/hqdefault.jpg | 1105 | 1.0% |
| https://i.ytimg.com/vi/ifceyul6gzy/hqdefault.jpg | 1046 | 0.9% |
| https://i.ytimg.com/vi/rrsrkf9eqxc/hqdefault.jpg | 1029 | 0.9% |
| https://i.ytimg.com/vi/4cpmb4tr2c4/hqdefault.jpg | 1015 | 0.9% |
| https://i.ytimg.com/vi/zf_q2v_9zky/hqdefault.jpg | 1005 | 0.9% |
| https://i.ytimg.com/vi/y_smu701qla/hqdefault.jpg | 974 | 0.9% |
| https://i.ytimg.com/vi/axp1cl0yafq/hqdefault.jpg | 973 | 0.9% |
| https://i.ytimg.com/vi/tv1e22u2cok/hqdefault.jpg | 951 | 0.9% |
| https://i.ytimg.com/vi/sq5tnvjwv6a/hqdefault.jpg | 947 | 0.8% |
| Other values (213) | 101290 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
Views
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONSKEWEDZEROS| Distinct | 1545 |
|---|---|
| Distinct (%) | 1.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 49.71428699 |
| Minimum | 0 |
|---|---|
| Maximum | 35677 |
| Zeros | 1347 |
| Zeros (%) | 1.2% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 3 |
| median | 9 |
| Q3 | 28 |
| 95-th percentile | 151 |
| Maximum | 35677 |
| Range | 35677 |
| Interquartile range (IQR) | 25 |
Descriptive statistics
| Standard deviation | 316.5575147 |
|---|---|
| Coefficient of variation (CV) | 6.367536051 |
| Kurtosis | 3395.060358 |
| Mean | 49.71428699 |
| Median Absolute Deviation (MAD) | 7 |
| Skewness | 43.93953763 |
| Sum | 5560891 |
| Variance | 100208.6601 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 1 | 13806 | 12.3% |
| 2 | 9821 | 8.8% |
| 3 | 7404 | 6.6% |
| 4 | 5894 | 5.3% |
| 5 | 4841 | 4.3% |
| 6 | 4086 | 3.7% |
| 7 | 3685 | 3.3% |
| 8 | 3313 | 3.0% |
| 9 | 3016 | 2.7% |
| 10 | 2782 | 2.5% |
| Other values (1535) | 53209 |
| Value | Count | Frequency (%) |
| 0 | 1347 | 1.2% |
| 1 | 13806 | |
| 2 | 9821 | |
| 3 | 7404 | |
| 4 | 5894 | |
| 5 | 4841 | 4.3% |
| 6 | 4086 | 3.7% |
| 7 | 3685 | 3.3% |
| 8 | 3313 | 3.0% |
| 9 | 3016 | 2.7% |
| Value | Count | Frequency (%) |
| 35677 | 1 | |
| 31473 | 1 | |
| 26668 | 1 | |
| 20341 | 1 | |
| 16144 | 1 | |
| 15410 | 1 | |
| 15235 | 1 | |
| 14585 | 1 | |
| 14419 | 1 | |
| 13875 | 1 |
Video Likes Added
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONSKEWEDZEROS| Distinct | 272 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2.095532689 |
| Minimum | 0 |
|---|---|
| Maximum | 1610 |
| Zeros | 69081 |
| Zeros (%) | 61.8% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 1 |
| 95-th percentile | 6 |
| Maximum | 1610 |
| Range | 1610 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 14.26369466 |
|---|---|
| Coefficient of variation (CV) | 6.806715418 |
| Kurtosis | 2511.935989 |
| Mean | 2.095532689 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 36.19381899 |
| Sum | 234400 |
| Variance | 203.4529854 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0 | 69081 | |
| 1 | 20179 | 18.0% |
| 2 | 7917 | 7.1% |
| 3 | 4146 | 3.7% |
| 4 | 2486 | 2.2% |
| 5 | 1642 | 1.5% |
| 6 | 1056 | 0.9% |
| 7 | 798 | 0.7% |
| 8 | 514 | 0.5% |
| 9 | 417 | 0.4% |
| Other values (262) | 3621 | 3.2% |
| Value | Count | Frequency (%) |
| 0 | 69081 | |
| 1 | 20179 | 18.0% |
| 2 | 7917 | 7.1% |
| 3 | 4146 | 3.7% |
| 4 | 2486 | 2.2% |
| 5 | 1642 | 1.5% |
| 6 | 1056 | 0.9% |
| 7 | 798 | 0.7% |
| 8 | 514 | 0.5% |
| 9 | 417 | 0.4% |
| Value | Count | Frequency (%) |
| 1610 | 1 | |
| 1227 | 1 | |
| 774 | 1 | |
| 711 | 1 | |
| 709 | 1 | |
| 657 | 1 | |
| 656 | 1 | |
| 631 | 1 | |
| 626 | 1 | |
| 613 | 1 |
| Distinct | 27 |
|---|---|
| Distinct (%) | < 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.05242407717 |
| Minimum | 0 |
|---|---|
| Maximum | 289 |
| Zeros | 109015 |
| Zeros (%) | 97.5% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 0 |
| Maximum | 289 |
| Range | 289 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 1.852012656 |
|---|---|
| Coefficient of variation (CV) | 35.3275204 |
| Kurtosis | 20793.11136 |
| Mean | 0.05242407717 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 139.9320946 |
| Sum | 5864 |
| Variance | 3.429950876 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=27)
| Value | Count | Frequency (%) |
| 0 | 109015 | |
| 1 | 2176 | 1.9% |
| 2 | 370 | 0.3% |
| 3 | 119 | 0.1% |
| 4 | 69 | 0.1% |
| 5 | 34 | < 0.1% |
| 6 | 14 | < 0.1% |
| 9 | 12 | < 0.1% |
| 7 | 10 | < 0.1% |
| 8 | 7 | < 0.1% |
| Other values (17) | 31 | < 0.1% |
| Value | Count | Frequency (%) |
| 0 | 109015 | |
| 1 | 2176 | 1.9% |
| 2 | 370 | 0.3% |
| 3 | 119 | 0.1% |
| 4 | 69 | 0.1% |
| 5 | 34 | < 0.1% |
| 6 | 14 | < 0.1% |
| 7 | 10 | < 0.1% |
| 8 | 7 | < 0.1% |
| 9 | 12 | < 0.1% |
| Value | Count | Frequency (%) |
| 289 | 2 | |
| 284 | 1 | |
| 269 | 1 | |
| 202 | 1 | |
| 64 | 1 | |
| 48 | 1 | |
| 36 | 1 | |
| 35 | 1 | |
| 32 | 1 | |
| 28 | 1 |
| Distinct | 29 |
|---|---|
| Distinct (%) | < 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.08678938287 |
| Minimum | 0 |
|---|---|
| Maximum | 420 |
| Zeros | 106332 |
| Zeros (%) | 95.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 0 |
| Maximum | 420 |
| Range | 420 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 1.793531685 |
|---|---|
| Coefficient of variation (CV) | 20.66533516 |
| Kurtosis | 41055.01462 |
| Mean | 0.08678938287 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 190.5669346 |
| Sum | 9708 |
| Variance | 3.216755906 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=29)
| Value | Count | Frequency (%) |
| 0 | 106332 | |
| 1 | 4160 | 3.7% |
| 2 | 678 | 0.6% |
| 3 | 284 | 0.3% |
| 4 | 168 | 0.2% |
| 5 | 107 | 0.1% |
| 6 | 39 | < 0.1% |
| 7 | 35 | < 0.1% |
| 8 | 13 | < 0.1% |
| 9 | 10 | < 0.1% |
| Other values (19) | 31 | < 0.1% |
| Value | Count | Frequency (%) |
| 0 | 106332 | |
| 1 | 4160 | 3.7% |
| 2 | 678 | 0.6% |
| 3 | 284 | 0.3% |
| 4 | 168 | 0.2% |
| 5 | 107 | 0.1% |
| 6 | 39 | < 0.1% |
| 7 | 35 | < 0.1% |
| 8 | 13 | < 0.1% |
| 9 | 10 | < 0.1% |
| Value | Count | Frequency (%) |
| 420 | 1 | |
| 355 | 1 | |
| 151 | 1 | |
| 74 | 1 | |
| 53 | 1 | |
| 38 | 1 | |
| 31 | 1 | |
| 25 | 1 | |
| 23 | 1 | |
| 20 | 1 |
User Subscriptions Added
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONSKEWEDZEROS| Distinct | 198 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1.169180293 |
| Minimum | 0 |
|---|---|
| Maximum | 1844 |
| Zeros | 86412 |
| Zeros (%) | 77.3% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 3 |
| Maximum | 1844 |
| Range | 1844 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 12.10906503 |
|---|---|
| Coefficient of variation (CV) | 10.35688431 |
| Kurtosis | 8300.19818 |
| Mean | 1.169180293 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 70.58319419 |
| Sum | 130781 |
| Variance | 146.629456 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0 | 86412 | |
| 1 | 13416 | 12.0% |
| 2 | 4322 | 3.9% |
| 3 | 2134 | 1.9% |
| 4 | 1258 | 1.1% |
| 5 | 839 | 0.8% |
| 6 | 604 | 0.5% |
| 7 | 435 | 0.4% |
| 8 | 304 | 0.3% |
| 9 | 251 | 0.2% |
| Other values (188) | 1882 | 1.7% |
| Value | Count | Frequency (%) |
| 0 | 86412 | |
| 1 | 13416 | 12.0% |
| 2 | 4322 | 3.9% |
| 3 | 2134 | 1.9% |
| 4 | 1258 | 1.1% |
| 5 | 839 | 0.8% |
| 6 | 604 | 0.5% |
| 7 | 435 | 0.4% |
| 8 | 304 | 0.3% |
| 9 | 251 | 0.2% |
| Value | Count | Frequency (%) |
| 1844 | 1 | |
| 1590 | 1 | |
| 803 | 1 | |
| 741 | 1 | |
| 718 | 1 | |
| 685 | 1 | |
| 630 | 1 | |
| 587 | 1 | |
| 571 | 1 | |
| 533 | 1 |
| Distinct | 18 |
|---|---|
| Distinct (%) | < 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.0263908383 |
| Minimum | 0 |
|---|---|
| Maximum | 32 |
| Zeros | 110050 |
| Zeros (%) | 98.4% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 0 |
| Maximum | 32 |
| Range | 32 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 0.3139080244 |
|---|---|
| Coefficient of variation (CV) | 11.8945833 |
| Kurtosis | 1766.305574 |
| Mean | 0.0263908383 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 31.48082153 |
| Sum | 2952 |
| Variance | 0.09853824779 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=18)
| Value | Count | Frequency (%) |
| 0 | 110050 | |
| 1 | 1384 | 1.2% |
| 2 | 215 | 0.2% |
| 3 | 72 | 0.1% |
| 4 | 41 | < 0.1% |
| 5 | 27 | < 0.1% |
| 6 | 18 | < 0.1% |
| 7 | 11 | < 0.1% |
| 9 | 10 | < 0.1% |
| 8 | 9 | < 0.1% |
| Other values (8) | 20 | < 0.1% |
| Value | Count | Frequency (%) |
| 0 | 110050 | |
| 1 | 1384 | 1.2% |
| 2 | 215 | 0.2% |
| 3 | 72 | 0.1% |
| 4 | 41 | < 0.1% |
| 5 | 27 | < 0.1% |
| 6 | 18 | < 0.1% |
| 7 | 11 | < 0.1% |
| 8 | 9 | < 0.1% |
| 9 | 10 | < 0.1% |
| Value | Count | Frequency (%) |
| 32 | 1 | < 0.1% |
| 21 | 1 | < 0.1% |
| 16 | 3 | < 0.1% |
| 15 | 1 | < 0.1% |
| 13 | 3 | < 0.1% |
| 12 | 4 | < 0.1% |
| 11 | 3 | < 0.1% |
| 10 | 4 | < 0.1% |
| 9 | 10 | |
| 8 | 9 |
| Distinct | 109659 |
|---|---|
| Distinct (%) | 99.2% |
| Missing | 1347 |
| Missing (%) | 1.2% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.3504564736 |
| Minimum | 0 |
|---|---|
| Maximum | 8.476339587 |
| Zeros | 80 |
| Zeros (%) | 0.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0.02200806075 |
| Q1 | 0.1780102378 |
| median | 0.3368243939 |
| Q3 | 0.4762565232 |
| 95-th percentile | 0.7813672404 |
| Maximum | 8.476339587 |
| Range | 8.476339587 |
| Interquartile range (IQR) | 0.2982462854 |
Descriptive statistics
| Standard deviation | 0.232565626 |
|---|---|
| Coefficient of variation (CV) | 0.663607733 |
| Kurtosis | 20.62733331 |
| Mean | 0.3504564736 |
| Median Absolute Deviation (MAD) | 0.1491538044 |
| Skewness | 1.537137424 |
| Sum | 38728.9449 |
| Variance | 0.05408677038 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 1 | 86 | 0.1% |
| 0 | 80 | 0.1% |
| 0.9831568627 | 27 | < 0.1% |
| 0.996672043 | 22 | < 0.1% |
| 0.9974185393 | 21 | < 0.1% |
| 0.9968543307 | 16 | < 0.1% |
| 0.997875 | 15 | < 0.1% |
| 0.9989321429 | 15 | < 0.1% |
| 0.9983235294 | 14 | < 0.1% |
| 0.9995510511 | 13 | < 0.1% |
| Other values (109649) | 110201 | |
| (Missing) | 1347 | 1.2% |
| Value | Count | Frequency (%) |
| 0 | 80 | |
| 3.311258278 × 10-6 | 1 | < 0.1% |
| 4.426737494 × 10-6 | 1 | < 0.1% |
| 8.426966292 × 10-6 | 1 | < 0.1% |
| 1.805054152 × 10-5 | 1 | < 0.1% |
| 1.812688822 × 10-5 | 1 | < 0.1% |
| 1.988466892 × 10-5 | 1 | < 0.1% |
| 2.102102102 × 10-5 | 1 | < 0.1% |
| 2.213368747 × 10-5 | 1 | < 0.1% |
| 3.979591837 × 10-5 | 1 | < 0.1% |
| Value | Count | Frequency (%) |
| 8.476339587 | 1 | |
| 6.081182796 | 1 | |
| 4.126801354 | 1 | |
| 3.934207156 | 1 | |
| 3.901702736 | 1 | |
| 3.885998526 | 1 | |
| 2.943820225 | 1 | |
| 2.837104545 | 1 | |
| 2.671567044 | 1 | |
| 2.59559322 | 1 |
| Distinct | 106978 |
|---|---|
| Distinct (%) | 96.8% |
| Missing | 1347 |
| Missing (%) | 1.2% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 216.7694276 |
| Minimum | 0 |
|---|---|
| Maximum | 5322.3 |
| Zeros | 80 |
| Zeros (%) | 0.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 874.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 17.835 |
| Q1 | 117.3790804 |
| median | 181.505 |
| Q3 | 268.1268875 |
| 95-th percentile | 520.7164244 |
| Maximum | 5322.3 |
| Range | 5322.3 |
| Interquartile range (IQR) | 150.7478071 |
Descriptive statistics
| Standard deviation | 190.7096512 |
|---|---|
| Coefficient of variation (CV) | 0.8797811266 |
| Kurtosis | 68.09049549 |
| Mean | 216.7694276 |
| Median Absolute Deviation (MAD) | 73.09761538 |
| Skewness | 5.186095552 |
| Sum | 23955189.44 |
| Variance | 36370.17106 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0 | 80 | 0.1% |
| 1 | 39 | < 0.1% |
| 2.9 | 28 | < 0.1% |
| 50.141 | 27 | < 0.1% |
| 0.9 | 25 | < 0.1% |
| 3 | 24 | < 0.1% |
| 4 | 23 | < 0.1% |
| 1.9 | 22 | < 0.1% |
| 2 | 22 | < 0.1% |
| 185.381 | 22 | < 0.1% |
| Other values (106968) | 110198 | |
| (Missing) | 1347 | 1.2% |
| Value | Count | Frequency (%) |
| 0 | 80 | |
| 0.001 | 1 | < 0.1% |
| 0.003 | 1 | < 0.1% |
| 0.014 | 1 | < 0.1% |
| 0.017 | 1 | < 0.1% |
| 0.018 | 1 | < 0.1% |
| 0.02 | 3 | < 0.1% |
| 0.024 | 1 | < 0.1% |
| 0.035 | 1 | < 0.1% |
| 0.036 | 1 | < 0.1% |
| Value | Count | Frequency (%) |
| 5322.3 | 1 | |
| 5028.021 | 1 | |
| 5028 | 1 | |
| 5027.66 | 1 | |
| 4701.785 | 1 | |
| 4517.889 | 1 | |
| 4517.15 | 1 | |
| 4517.097 | 1 | |
| 4517.081 | 1 | |
| 4224.958 | 1 |
| Distinct | 1 |
|---|---|
| Distinct (%) | < 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 874.0 KiB |
| 0 |
|---|
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 111857 |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| 0 | 111857 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here. A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.
First rows
| Date | Video Title | External Video ID | Video Length | Thumbnail link | Views | Video Likes Added | Video Dislikes Added | Video Likes Removed | User Subscriptions Added | User Subscriptions Removed | Average View Percentage | Average Watch Time | User Comments Added | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 19 Jan 2022 | Kaggle Project From Scratch - Part 2 (Exploratory Data Analysis) | KQ80oD_boBM | 2191 | https://i.ytimg.com/vi/KQ80oD_boBM/hqdefault.jpg | 13 | 0 | 0 | 0 | 0 | 0 | 0.069055 | 151.300154 | 0 |
| 1 | 19 Jan 2022 | Welcome To My Channel | Ken Jee | Data Science | smeFkHwnM_k | 51 | https://i.ytimg.com/vi/smeFkHwnM_k/hqdefault.jpg | 2 | 0 | 0 | 0 | 1 | 0 | 0.471255 | 24.034000 | 0 |
| 2 | 19 Jan 2022 | How She Dominated the FAANG Data Science Interview (@Tina Huang ) - KNN EP. 11 | vfV4nm004VQ | 2686 | https://i.ytimg.com/vi/vfV4nm004VQ/hqdefault.jpg | 10 | 0 | 0 | 0 | 0 | 0 | 0.126049 | 338.567500 | 0 |
| 3 | 19 Jan 2022 | The 9 Books That Changed My Perspective in 2019 | 3TrAYmrmA8o | 980 | https://i.ytimg.com/vi/3TrAYmrmA8o/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.011508 | 11.278000 | 0 |
| 4 | 19 Jan 2022 | Interview with the Director of AI Research @ NVIDIA (Anima Anandkumar) - KNN EP. 07 | Xgg7dIKys9E | 2904 | https://i.ytimg.com/vi/Xgg7dIKys9E/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.007541 | 21.900000 | 0 |
| 5 | 19 Jan 2022 | Data Science, Machine Learning, and AI: What's the Difference? | q8cEt8gj3zY | 266 | https://i.ytimg.com/vi/q8cEt8gj3zY/hqdefault.jpg | 7 | 0 | 0 | 0 | 0 | 0 | 0.584489 | 155.474143 | 0 |
| 6 | 19 Jan 2022 | The PODCAST you might have asked for? | tnpV1etgcxs | 139 | https://i.ytimg.com/vi/tnpV1etgcxs/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.045813 | 6.368000 | 0 |
| 7 | 19 Jan 2022 | #66DaysOfData Round 3 Live Event! (feat. @StatQuest with Josh Starmer) | qUK5Vk4NvBw | 3735 | https://i.ytimg.com/vi/qUK5Vk4NvBw/hqdefault.jpg | 2 | 0 | 0 | 0 | 0 | 0 | 0.017095 | 63.850000 | 0 |
| 8 | 19 Jan 2022 | 5 Proven Strategies to Break into a Data Science Job | UpaEjBOMNqs | 334 | https://i.ytimg.com/vi/UpaEjBOMNqs/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.254341 | 84.950000 | 0 |
| 9 | 19 Jan 2022 | Reviewing Your Data Science Projects - Episode 7 (Incredible Portfolio Website) | txR8_jGi0Ls | 904 | https://i.ytimg.com/vi/txR8_jGi0Ls/hqdefault.jpg | 4 | 0 | 0 | 0 | 0 | 0 | 0.362091 | 327.330250 | 0 |
Last rows
| Date | Video Title | External Video ID | Video Length | Thumbnail link | Views | Video Likes Added | Video Dislikes Added | Video Likes Removed | User Subscriptions Added | User Subscriptions Removed | Average View Percentage | Average Watch Time | User Comments Added | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 111847 | 27 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.264855 | 82.370000 | 0 |
| 111848 | 26 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 3 | 0 | 0 | 0 | 0 | 0 | 0.509827 | 158.556333 | 0 |
| 111849 | 25 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.233846 | 72.726000 | 0 |
| 111850 | 24 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.872392 | 271.314000 | 0 |
| 111851 | 22 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 2 | 0 | 0 | 0 | 0 | 0 | 0.502150 | 156.168500 | 0 |
| 111852 | 21 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 2 | 0 | 0 | 0 | 0 | 0 | 0.693108 | 215.556500 | 0 |
| 111853 | 20 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 9 | 0 | 0 | 0 | 0 | 0 | 0.492501 | 153.167667 | 0 |
| 111854 | 19 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 4 | 0 | 0 | 0 | 0 | 0 | 0.087268 | 27.140250 | 0 |
| 111855 | 18 Nov 2017 | Predicting Crypto-Currency Price Using RNN lSTM & GRU | qfRhKHV8-t4 | 311 | https://i.ytimg.com/vi/qfRhKHV8-t4/hqdefault.jpg | 13 | 0 | 0 | 0 | 0 | 0 | 0.444176 | 138.138769 | 0 |
| 111856 | 1 Nov 2017 | ProjectDemoCSC478_UFCFightData | 5p73cIRYCZg | 729 | https://i.ytimg.com/vi/5p73cIRYCZg/hqdefault.jpg | 1 | 0 | 0 | 0 | 0 | 0 | 0.003018 | 2.200000 | 0 |